We follow the process used in VITON [1]} while creating our training and testing datasets from the publicly available DeepFashion dataset [2]}.
We use LCR-net++ [3]} for 2D human pose estimation, and Pytorch-MULA [4]} [5]} to get the parsing results for the models. The human parser [4]} is used to create data to train U-Net++ [7]}, to segment the garments from the models, and to remove the head from the models.
We have 14,221 training samples, as in the VITON dataset, and 900 paired samples for testing our method.
We note that the authors in VITON [1]} have used [9]} for human parsing and [10]} for 2D human pose estimation.
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